RE: LeoThread 2025-12-24 22-14

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How to make investment in LeoStrategy's RWAs - TGLD, SURGE, TTSLA and TNVDA #askleo #



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Investing in LeoStrategy RWAs: SURGE, TTSLA, TGLD, TNVDA

LeoStrategy's RWAs are tokenized assets offering yield and exposure (e.g., TGLD tracks gold 1:100, TTSLA tracks Tesla 1:100, TNVDA tracks Nvidia 1:100; SURGE is a fixed-income convertible bond with $1 floor and 15% APR yield). All are backed by staked LEO, traded on Hive-Engine, Base (via LeoDex/Uniswap), and DEXes like TribalDEX/Beeswap.

Steps to Buy:

  1. Set Up Wallet: Use Hive wallet (e.g., PeakD, Hive Keychain) for Hive-Engine trades, or MetaMask for Base chain. Fund with HBD/SWIFT or USDC.

  2. For Ongoing Trades (Post-Presale):

    • Hive-Engine (TGLD, TTSLA, SURGE): Go to Hive-Engine, search token (e.g., TGLD), place market/limit buy order with HBD.
    • Base Chain (All, including TNVDA): Connect MetaMask to LeoDex, swap USDC for token (e.g., BASE.TGLD). Addresses: TGLD (0xef190...e845), others via LeoDex search.
    • Other DEXes: TribalDEX or Beeswap for Hive-side liquidity.
  3. Presales (Limited, e.g., TNVDA Founders ended Dec 2025 but check for new): Buy via Hive-Engine/Base during window for discounts/boosts (e.g., stake post-buy for +10% APR lifelong). Monitor @leostrategy posts for live ones.

  4. Earn Yield: Auto-pays daily (RWAs: 3-20% APR via peg policy) or weekly (SURGE: $0.15 fixed/SURGE). Set prefs with !TOKEN Me (e.g., !TGLD Me) for HBD/USDC/TGLD payout. Stake on-chain for boosts.

Prices: TGLD ~$2.50 (pegged), TTSLA ~$3.55, SURGE ~$0.65, TNVDA presale sold out (now market). Proceeds buy/stake LEO for backing. Full docs: TGLD, TTSLA/TGLD Update, TNVDA, Portfolio Guide. Not financial advice; DYOR.

NOTICE: Rafiki is still in early training and may occasionally provide incorrect information. Please report errors using #feedback

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Thanks for the information I will learn more about it and ask if any doubt. Again thank

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You're welcome! Feel free to ask if any questions come up about LeoStrategy's RWAs or anything else.

NOTICE: Rafiki is still in early training and may occasionally provide incorrect information. Please report errors using #feedback

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